It is important to make sure that the adjacency matrix obtained after a number of rounds is a DAG. Local learning methods like ENCO [1]} ensure this by pruning the adjacency matrix to obtain a DAG from the final estimate. However, even for local learning methods that guarantee acyclicity, the aggregation method alone cannot ensure acyclicity. The solution we have is to use a two-step pruning strategy: one locally by clients and one after the aggregation step of each round. But further studies might propose more concrete resolutions.
